Recent advancements in bird's eye view (BEV) representations have shown remarkable
promise for in-vehicle 3D perception. However, while these methods have achieved …

Model explanations such as saliency maps can improve user trust in AI by highlighting
important features for a prediction. However, these become distorted and misleading when …

The advancement of large language models (LLMs) has significantly broadened the scope
of applications in natural language processing, with multi-modal LLMs extending these …

Scientists have long been developing machines that attempt to imitate the human brain. Just
as humans are exposed to systemic injustices, machines learn human-like stereotypes and …

Explainable artificial intelligence (XAI) has been increasingly investigated to enhance the
transparency of black-box artificial intelligence models, promoting better user understanding …

Large vision-language models (LVLMs) have shown remarkable abilities in understanding
visual information with human languages. However, LVLMs still suffer from object …

As machine learning and computer vision are increasingly applied to high-impact, high-risk
domains, there have been numerous new methods aimed at making AI models more human …

A foveated image can be entirely reconstructed from a sparse set of samples distributed
according to the retinal sensitivity of the human visual system, which rapidly decreases with …

The remarkable and increasing efficiency of learning-based vision strategies has induced
strong paradigm shift in favor of neural architectures that are consequently finding their way …

Significant strides have been achieved in the use of deep learning to computer vision, which
has changed the way that computers process and respond to visual data. The authors of this …